Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.5
3.2
Journals
Energies
Special Issues
Industry 4.0—from Smart Factory to Cognitive Cyberphysical Production System and...
energies-logo
Submit to Energies Review for Energies Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Industry 4.0—from Smart Factory to Cognitive Cyberphysical Production System and Cloud Manufacturing

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 21606

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editor

Prof. Dr. Marko Mladineo

E-Mail Website
Guest Editor
Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, Rudera Boskovica 32, 21000 Split, Croatia
Interests: production systems; production networks; cyberphysical production systems; multicriteria decision making; multi-objective optimization; Industry 4.0

Special Issue Information

Dear Colleagues,

It has been more than five years since the Industry 4.0 paradigm became a global research trend. From the beginning, it was clear that the Smart Factory concept would be its main enabler. Smart Factory was seen as a place where virtual and reality meet, supported by the Industrial Internet of Things and Cyberphysical Production System. However, it soon became clear that we need to take a step forward in our production cyberspace, toward a cognitive system. This is something that goes beyond the concept of smart, something more than big data analytics. A cognitive system can learn and adapt to new situations and to new market demands, completely autonomously or with some human support. A cognitive cyberphysical production system requires brand-new cognitive algorithms and decision-making systems.

Generally, the backend of such a system is a cloud-based information system known as cloud manufacturing. The design of such an information system, networked with ERP and MES, is a challenging task. Nevertheless, with a cognitive cyberphysical production system, new business models for the new era of personalized production become possible: manufacturing-as-a-service and production-as-a-service. Since they go beyond single enterprises and toward the networking of enterprises, they lead to new organizational models and platforms: production networks and social manufacturing. However, cognitive systems also raise some ethical issues, which is not common for production research problems. These ethical issues are their transparency, inclusion, responsibility, impartiality, reliability, security, and privacy. They represent an important research topic, especially to distinguish Industry 4.0 research from transhumanism ideas.

As a response to all these challenges, we have launched this Special Issue of the journal Energies on the topic of “Industry 4.0—from Smart Factory to Cognitive Cyberphysical Production System and Cloud Manufacturing”.

I invite you to submit your paper to this Special Issue and share your research with us and with the academic community. Potential topics include but are not limited to smart factory concepts and demonstrators, cyberphysical production system models and prototypes, cognitive systems applied to the manufacturing domain, cognitive algorithms and decision-making systems, applications of the Industrial Internet of Things, production network models and solutions, manufacturing-as-a-service and production-as-a-service platforms, cloud manufacturing models and demonstrators, and ethical issues regarding cognitive systems. In addition to research papers, review papers are welcomed as well.

Prof. Dr. Marko Mladineo
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Industry 4.0
  • Cyberphysical production system
  • Smart factory
  • Cognitive system
  • Production network
  • Social manufacturing
  • Industrial Internet of Things
  • Cloud manufacturing
  • Key enabling technologies
  • Manufacturing-as-a-service

Published Papers (6 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review

23 pages, 2533 KiB  
Article
Multi-Objective Optimization via GA Based on Micro Laser Line Scanning Data for Micro-Scale Surface Modeling
by J. Apolinar Muñoz Rodríguez
Energies 2022, 15(18), 6571; https://0-doi-org.brum.beds.ac.uk/10.3390/en15186571 - 08 Sep 2022
Viewed by 952
Abstract
Industry 4.0 represents high-level methodologies to make intelligent, autonomous, and self-adaptable manufacturing systems. Additionally, the surface modeling technology has become a great tool in industry 4.0 for representing the surface point cloud. Thus, the micro-scale machining technology requires efficient models to represent micro-scale [...] Read more.
Industry 4.0 represents high-level methodologies to make intelligent, autonomous, and self-adaptable manufacturing systems. Additionally, the surface modeling technology has become a great tool in industry 4.0 for representing the surface point cloud. Thus, the micro-scale machining technology requires efficient models to represent micro-scale flat and free-form surfaces. Therefore, it is fundamental to perform surface modeling through artificial intelligence for representing small surfaces. This study addressed multi-objective optimization via genetic algorithms and micro laser line projection to accomplish surface models for representing micro-scale flat and free-form surfaces, where an optical microscope system retrieves micro-scale topography via micro laser line coordinates and the multi-objective optimization constructs the flat and free-form surface models through genetic algorithms and micro-scale topography. The multi-objective optimization determines the surface model parameters through exploration and exploitation, and the solution space is deduced via surface data. The surface model generated through the multi-objective optimization fit accurately to the micro-scale target surface. Thus, the proposed technique enhanced the fitting of micro-scale flat and free-form surface models, which were deduced via gray-level images of an optical microscope. This enhancement was validated by a discussion between the multi-objective optimization via genetic algorithms and the micro-scale surface modeling via optical microscope imaging systems. Full article
(This article belongs to the Special Issue Industry 4.0—from Smart Factory to Cognitive Cyberphysical Production System and Cloud Manufacturing)
►▼ Show Figures

Figure 1

21 pages, 2284 KiB  
Article
Integrated Functional Safety and Cybersecurity Evaluation in a Framework for Business Continuity Management
by Kazimierz T. Kosmowski, Emilian Piesik, Jan Piesik and Marcin Śliwiński
Energies 2022, 15(10), 3610; https://0-doi-org.brum.beds.ac.uk/10.3390/en15103610 - 15 May 2022
Cited by 5 | Viewed by 3101
Abstract
This article outlines an integrated functional safety and cybersecurity evaluation approach within a framework for business continuity management (BCM) in energy companies, including those using Industry 4.0 business and technical solutions. In such companies, information and communication technology (ICT), and industrial automation and [...] Read more.
This article outlines an integrated functional safety and cybersecurity evaluation approach within a framework for business continuity management (BCM) in energy companies, including those using Industry 4.0 business and technical solutions. In such companies, information and communication technology (ICT), and industrial automation and control system (IACS) play important roles. Using advanced technologies in modern manufacturing systems and process plants can, however, create management impediments due to the openness of these technologies to external systems and networks via various communication channels. This makes company assets and resources potentially vulnerable to risks, e.g., due to cyber-attacks. In the BCM-oriented approach proposed here, both preventive and recovery activities are considered in light of engineering best practices and selected international standards, reports, and domain publications. Full article
(This article belongs to the Special Issue Industry 4.0—from Smart Factory to Cognitive Cyberphysical Production System and Cloud Manufacturing)
►▼ Show Figures

Figure 1

22 pages, 6579 KiB  
Article
Multi-Criteria Decision Support System for Smart and Sustainable Machining Process
by Luka Celent, Marko Mladineo, Nikola Gjeldum and Marina Crnjac Zizic
Energies 2022, 15(3), 772; https://0-doi-org.brum.beds.ac.uk/10.3390/en15030772 - 21 Jan 2022
Cited by 8 | Viewed by 1928
Abstract
Sustainatableble development assumes the meeting of humanity’s everyday needs and development goals while sustaining the ability of nature to provide the resources and ecosystem on which the economy and society depend. It means that an increase of economic benefit cannot be a single [...] Read more.
Sustainatableble development assumes the meeting of humanity’s everyday needs and development goals while sustaining the ability of nature to provide the resources and ecosystem on which the economy and society depend. It means that an increase of economic benefit cannot be a single optimization problem anymore, instead, the multi-criteria approach is used with the accent on ecology and social welfare. However, it is not easy to harmonize these aims with machining, which is a well known industrial pollutant. On the other hand, new industrial paradigms such as Industry 4.0/5.0, are driving toward the smart concept that collects data from the manufacturing process and optimizes it in accordance with productivity and/or ecologic aims. In this research, the smart concept is used through the development of the multi-criteria decision support system for the selection of the optimal machining process in terms of sustainability. In the case of milling process selection, it has been demonstrated that green machining, without a multi-criteria approach, will always remain an interesting research option, but not a replacement for conventional machining. However, when applying realistic ecological and social criteria, green machining becomes a first choice imperative. The multi-criteria decision-making PROMETHEE method is used for the comparison and ranking, and validation of results is made through criteria weights sensitivity analysis. The contribution of this concept is that it could also be applied to other manufacturing processes. Full article
(This article belongs to the Special Issue Industry 4.0—from Smart Factory to Cognitive Cyberphysical Production System and Cloud Manufacturing)
►▼ Show Figures

Figure 1

20 pages, 3046 KiB  
Article
Optimization of Industry 4.0 Implementation Selection Process towards Enhancement of a Manual Assembly Line
by Amanda Aljinović, Nikola Gjeldum, Boženko Bilić and Marko Mladineo
Energies 2022, 15(1), 30; https://0-doi-org.brum.beds.ac.uk/10.3390/en15010030 - 21 Dec 2021
Cited by 7 | Viewed by 3362
Abstract
Last year’s developments are characterized by a dramatic drop in customer demand leading to stiff competition and more challenges that each enterprise needs to cope with in a globalized market. Production in low-mix/high-volume batches is replaced with low-volume/high-variety production, which demands excessive information [...] Read more.
Last year’s developments are characterized by a dramatic drop in customer demand leading to stiff competition and more challenges that each enterprise needs to cope with in a globalized market. Production in low-mix/high-volume batches is replaced with low-volume/high-variety production, which demands excessive information flow throughout production facilities. To cope with the excessive information flow, this production paradigm requires the integration of new advanced technology within production that enables the transformation of production towards smart production, i.e., towards Industry 4.0. The procedure that helps the decision-makers to select the most appropriate I4.0 technology to integrate within the current assembly line considering the expected outcomes of KPIs are not significantly been the subject of the research in the literature. Therefore, this research proposes a conceptual procedure that focus on the current state of the individual assembly line and proposes the technology to implement. The proposed solution is aligned with the expected strategic goals of the company since procedure takes into consideration value from the end-user perspective, current production plans, scheduling, throughput, and other relevant manufacturing metrics. The validation of the method was conducted on a real assembly line. The results of the validation study emphasize the importance of the individual approach for each assembly line since the preferences of the user as well as his diversified needs and possibilities affect the optimal technology selection. Full article
(This article belongs to the Special Issue Industry 4.0—from Smart Factory to Cognitive Cyberphysical Production System and Cloud Manufacturing)
►▼ Show Figures

Figure 1

17 pages, 13657 KiB  
Article
The Concept of Cyber-Physical Networks of Small and Medium Enterprises under Personalized Manufacturing
by Sebastian Saniuk and Sandra Grabowska
Energies 2021, 14(17), 5273; https://0-doi-org.brum.beds.ac.uk/10.3390/en14175273 - 25 Aug 2021
Cited by 10 | Viewed by 1703
Abstract
The era of Industry 4.0 is characterized by the use of new telecommunications ICT technologies and networking of the economy. This results in changes both in the way businesses operate and in customer expectations of products offered on the market. The use of [...] Read more.
The era of Industry 4.0 is characterized by the use of new telecommunications ICT technologies and networking of the economy. This results in changes both in the way businesses operate and in customer expectations of products offered on the market. The use of modern ICT technologies has made it possible to create cyber-physical systems based on intelligent machines and devices that communicate with each other in real time and allow the integration of resources from different companies to carry out joint production projects. Today’s consumer expects products tailored to their needs and expectations. These expectations can be met by leveraging the potential of highly specialized manufacturing service companies centered around e-business platforms. The article presents the results of research using bibliometric analysis and the results of surveys conducted among small and medium-sized enterprises. The concept of e-business platforms supporting rapid prototyping of temporary networks of companies capable of manufacturing personalized products in the environment of Industry 4.0 is presented. The task of the platform is to integrate a customer expecting personalized production with a network of companies having adequate production resources. Full article
(This article belongs to the Special Issue Industry 4.0—from Smart Factory to Cognitive Cyberphysical Production System and Cloud Manufacturing)
►▼ Show Figures

Figure 1

Review

Jump to: Research

20 pages, 2667 KiB  
Review
From Industry 4.0 towards Industry 5.0: A Review and Analysis of Paradigm Shift for the People, Organization and Technology
by Marina Crnjac Zizic, Marko Mladineo, Nikola Gjeldum and Luka Celent
Energies 2022, 15(14), 5221; https://0-doi-org.brum.beds.ac.uk/10.3390/en15145221 - 19 Jul 2022
Cited by 88 | Viewed by 9444
Abstract
The industry is a key driver of economic development. However, changes caused by introduction of modern technologies, and increasing complexity of products and production, directly affect the industrial enterprises and workers. The critics of the Industry 4.0 paradigm emphasized its orientation to new [...] Read more.
The industry is a key driver of economic development. However, changes caused by introduction of modern technologies, and increasing complexity of products and production, directly affect the industrial enterprises and workers. The critics of the Industry 4.0 paradigm emphasized its orientation to new technologies and digitalization in a technocratic way. Therefore, the new industrial paradigm Industry 5.0 appeared very soon and automatically triggered a debate about the role of, and reasons for applying, the new paradigm. Industry 5.0 is complementing the existing Industry 4.0 paradigm with the orientation to the worker who has an important role in the production process, and that role has been emphasized during the COVID-19 pandemic. In this research, there is a brief discussion on main drivers and enablers for introduction of these new paradigms, then a literature-based analysis is carried out to highlight the differences between two paradigms from three important aspects—people, organization, and technology. The conclusion emphasizes the main features and concerns regarding the movement towards Industry 5.0, and the general conclusion is that there is a significant change of the main research aims from sustainability towards human-centricity. At the end, the analysis of maturity models that evaluates enterprises’ readiness to introduce features of new paradigms is given as well. Full article
(This article belongs to the Special Issue Industry 4.0—from Smart Factory to Cognitive Cyberphysical Production System and Cloud Manufacturing)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-6
Back to TopTop